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BackgroundSelf-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established. ObjectiveWe examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method. MethodsA total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices. ResultsOn the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=−.13 to .37) and Spearman (ρ=−.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw. ConclusionsMost wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

Scientific research on forest therapy's preventive medical and mental health effects has advanced, but the need for clear evidence for practical applications remains. We conducted an unblinded randomized controlled trial involving healthy men aged 40–70 to compare the physiological and psychological effects of forest and urban walking. Eighty-four participants were randomly assigned to either the forest or urban group, with 78 completing 90-min walks and analysis. The primary outcome measured was the change in saliva-secreted immunoglobulin A (sIgA) levels. Evaluating researchers were blinded to the groups, but participants and on-site staff were not. Here, we demonstrate a significant increase in saliva-secreted immunoglobulin A (sIgA) levels in the forest group. Furthermore, forest walking resulted in improved mood, including a reduction in stress hormone levels. In conclusion, mindful forest walking has the potential to enhance immunity and promote health. Clinical trial registration: University Hospital Medical Information Network. Trail registration number: UMIN000045851. Approval date: 25/10/2021. [ABSTRACT FROM AUTHOR]

Physical inactivity contributes to various health risks; however, approximately one-third of the global population remains insufficiently active. Many researchers have attempted to increase physical activity levels; however, the effectiveness and the specific components of these interventions remain unclear. This systematic review with meta-analyses utilized a behavior change technique taxonomy to identify and extract effective intervention components, aiming to develop more efficient programs to promote physical activity. We searched the PubMed and Ichu-shi Web databases for studies targeting healthy young and middle-aged adults with data on physical activity changes and extracted the intervention components. A random-effects model was used for the primary meta-analysis, and a meta-regression was conducted for the selected outcomes. Overall, 116 studies were included, with 102 used for the primary analysis. The interventions showed a small effect on overall physical activity promotion. Subsequent meta-regressions identified 1.5 Review behavior goal(s) as a significant positive intervention component, as well as four and three potential positive and negative components, respectively. This systematic review and meta-analysis demonstrated the effectiveness of physical activity interventions and highlighted effective and negative components. These findings may inform the design of future programs aimed at promoting physical activity. [ABSTRACT FROM AUTHOR]

Overweight and obesity have reached epidemic proportions worldwide. The COVID-19 pandemic resulted in an increased need for remote implementation of weight-loss interventions; therefore, the effectiveness of web-based interventions needed to be assessed. This study aimed to examine the effectiveness of web-based interventions and their potency in facilitating weight changes in adults who were overweight or obese. We searched PubMed and Ichu-shi Web from the first year of inclusion in each database until the search date (30 September 2020). Among 1466 articles retrieved from the two databases and manual search, 97 were selected to undergo qualitative analysis and 51 articles were subjected to quantitative analysis. Qualitative analysis of 97 articles demonstrated that articles showing significant effectiveness mostly used the following components: social support, self-monitoring for behavior, self-monitoring for the outcome (weight), behavioral goal setting, information about health consequences, and outcome goal setting. Quantitative analysis of 51 articles showed a significant effectiveness of web-based intervention (standardized mean difference, −0.57; 95% confidence interval, −0.75 to −0.40). This study demonstrated the effectiveness of web-based interventions on weight change in adults with overweight and obesity. Subgroup meta-analyses identified personalized information provision and expert advice to be remarkably effective components. [ABSTRACT FROM AUTHOR]